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Why should you learn R programming language?

The importance of Big data is on an ever-increasing trend and as more and more Software as a service companies prefer it, it is becoming a great playfield for professionals to come in and earn big bucks. The field of Big Data analytics is emerging as a great rewarding option both in terms of learning and earning.
In order to initiate of boost a career in the Big Data and data science industry, it is wise to learn a programming language that will aid in big data analysis. Out of numerous language options, R is a great choice.

Designed by statisticians, R is tailor-made to suit statistical computing. With the improvement in technology, researched data is increasing in complexity and thus R is being preferred more for data analysis. It is a comprehensive approach that greatly serves the purpose of machine learning, data visualization and analysis.

Here is how learning R can be a great boost to your career:

It offers a great tool to statisticians and hence all data scientists can benefit from it for they are passionate programmers cum statisticians

R has established itself as a standard among all statistical programming languages

R programming language is accepted in the industry as a coveted skill. Big data analysts and data scientists with knowledge of R, are in great demand for employment at big brands such as Google, Facebook etc.

It is a very versatile language that is diversifying its commercial applications each day

Some features that make it a highly functional and amazing language are as follows:

R offers great cross-platform compatibility

It is versatile in terms of operating systems and works seamlessly on Windows, Mac OSX and Linux

It is compatible with database programs such as Microsoft Excel access, MySQL, SQLite, Oracle etc. It is easy to import data.

It offers great scripting support as it can handle huge data volumes, complex in nature.

High-performance computers and simulations requiring resources can be managed perfectly with R.

It is majorly accepted and quite popular in the programming languages space.
It is highly receptible to change. All major statistics developments reflect initially as R packages

It can be easily combined with document preparation systems. This implies that output and graphics from R can be combined with word-processing documents.

The resource bank and R community are quite large. A huge community of R users is pretty active on forums and physical conferences.

It has a huge library space with over 2000 libraries that can be used unlimited and cover statistics in areas such as finance, computing etc.

The scope of R is high because it is not very easily understandable and not many people are well versed with the syntax and rules. It has a steep learning curve owing to difficult syntax, rules and symbol definitions. It is not readable like English.
The inbuilt functions and tools make R capable of performing all tasks in a straightforward way. R is perfect for statistical computing and data visualization is better and more convenient with R than python.

Despite the comprehensive features and awesome statistical support that R offers, it also faces certain scalability issues. They are as below:

Low speed: The basic design of R is not supposed to be fast and is thus annoying when large datasets are operated upon for analysis. It however does not impact functionality as R projects cannot be easily integrated into web apps.

Memory limitations: Analyzing huge datasets is quite resource expensive because R uses huge chunks of memory that uses harddrive if RAM isn’t very large. This may make the computation even slower.

Huge passionate community:

As a passionate programmer you can derive immense support from the huge community that R has. All developer communities function by giving and taking help as it helps to build useful tools that make coding in that language easier. Here are some facts about the R community:

R is a popular language on StackOverflow. It is the 11th most followed and it is important because a lot of coders use it as a go-to for their programming queries and networking.

Networking and learning with fellow coders are easy when you have a platform to meetup. These meetups also offer amazing mentoring opportunities. R has the 8th largest meetup community made up of over 130000 members around the world. It is a pretty active community despite not being comparable in size to other huge communities.

A large volume of GitHub Projects:
R boasts of over 199000 GitHub products which may not seem to be huge as compared to Python. One of the features that strengthen R greatly is its CRAN repository that addresses all data analysis needs with over 7700 packages. These packages are highly sophisticated and hence the quality of R tools is pretty high and greatly functional.

Wide career opportunities:
With the rise in the amount of data gathered by companies, the demand for data scientists is also on the rise. The demand for R developers is certainly going to increase as it is a great tool for data analysis.

R enables tapping the complete potential of data analysis for helping businesses maintain a good rapport with customers. The TIOBE Index indicates R as 18th most popular language.

Google trends also indicate a significant rise in the number of R enthusiasts. It is a great tide to get on in order to get a position in the data analysis and statistics space and learning the language is promising on many levels. It not only offers a great career but also provides sustained support throughout the career. It is a good opportunity to look at though it may require considerable effort to learn.